Many users demand efficiency in their online interactions and expect to obtain the information they need from their computing devices in the shortest possible amount of time. It can be challenging and even frustrating for these users to find the information they need in a computing system quickly. One reason for this is that conventional search engines often treat the user's query as a set of keywords, with little or no effort to interpret the underlying meaning or connotation of the user's request. As a result, it may take a person several attempts at searching to find the desired information, or the search effort may even end in failure.
In addition, many people are accustomed to using very short phrases, abbreviations, acronyms, truncated words, or their own ‘shorthand,’ in their computing activity. This is often a result of the desire for speed and the small size and limited keyboard of many mobile computing devices. The increasing popularity of text messaging and online services such as TWITTER, LINKEDIN, and/or other applications that impose character limits may also encourage brevity. Moreover, whether or not a search request is particularly succinct, it may contain terms that have a special meaning or connotation, which is personal to the particular user but which may not be readily discernible using traditional query analysis techniques.
Some electronic search systems have used public dictionaries, query logs, search engine usage characteristics, crowd sourcing and/or consensus relevancy methods in an effort to better resolve the intention of a search request. However, these tools and techniques typically are not well equipped to determine when a search term has a user-specific meaning or connotation, or to determine the user-specific meaning of a search term. As a result, the search may return results that have little or no relevance to the information the user was seeking.
With the incorporation of Global Positioning Systems (GPS) or similar technology into many computing devices, search engines may now have access to useful information about the user's current geographic location and nearby people, places or things. Such information can be used to improve or enhance search results where current geographic location is a relevant aspect of the information desired (e.g., a search for local stores, gasoline stations, etc.). However, without more, this information may be of little utility more generally, e.g. for searches that are not primarily location-oriented.